Abstract:
Record linking joins records from one or more data sets that pertain to the same entity or event. Record linkage compares ensembles of partially-identifying, non-unique data elements between pairs of records without a common, unique key. To make accurate comparisons, variable data like names and addresses must be processed and standardized.
Deterministic rule-based data processing systems have traditionally performed this pre-processing, known as “standardization”. This project proposes standardization utilizing lexicon-based tokenization and probabilistic Hidden Markov Models. Visual Studio and C#.Net are used to develop the project. The only user with system access is admin.
Administrators can only access the system after logging in. After logging in, admin can add training data by filling out all registration sections. Administration will be required to randomly populate information fields when assessing data.
Information tab incoming data is unstructured and must be formatted. After entering random data in the random field, admin can analyze the entered data, which the algorithm will process and present in an organized format.
Note: Please discuss with our team before submitting this abstract to the college. This Abstract or Synopsis varies based on student project requirements.
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